Dialogue Act Classification Exploiting Lexical Semantics
Nicole Novielli, Carlo Strapparava · IGI Global eBooks · 2011
In this chapter we present our experience with automatic dialogue act recognition using empirical methods for exploiting lexical semantics in an unsupervised framework. Moreover, we show how automatic dialogue act annotation of human-ECA (Embodied Conversational Agent) interactions may be used as a preliminary step in conversational analysis for modeling the users’ attitudes. Experiments are presented, by exploiting corpora of English and Italian natural dialogues. In both cases the approaches employed have been conceived as general and domain-independent and may be relevant to a wide range of both human-computer and human-human interaction application domains.